Prediction rule for characterization of hepatic lesions revealed on MR imaging: estimation of malignancy.

Prediction rule for characterization of hepatic lesions revealed on MR imaging: estimation of malignancy. Research Abstract Details 

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Prediction rule for characterization of hepatic lesions revealed on MR imaging: estimation of malignancy. Abstract Text:

R Tello,H M Fenlon,T Gagliano,V L deCarvalho,E K Yucel,

OBJECTIVE: Our aims were to establish factors that are most predictive of hepatic lesion malignancy and to formulate a prediction rule. MATERIALS AND METHODS: A cross-sectional study of 227 abdominal MR imaging examinations revealed 85 lesions in 67 patients (29 men, 38 women; age range, 29-78 years; mean age, 51.4 years) who were being examined for primary malignancy (n = 42) or unknown lesion characterization (n = 25). All were referred for MR imaging after CT or sonography. Patient demographics (age, sex, history of malignancy), lesion size and morphology, quantitative T2 calculation, and pattern of enhancement on gadopentetate dimeglumine administration were evaluated for predictive ability. RESULTS: Thirty-two liver lesions were malignant (eight colon cancer, five breast cancer, four cervical cancer, three renal cancer, three lung cancer, and nine miscellaneous cancers), 53 were benign (37 hemangiomas, 15 cysts, and one focal nodular hyperplasia). Calculated T2 relaxation times (mean +/- standard deviation [SD]) were as follows: malignant tumors (91.72 +/- 21.9 msec), hemangiomas (136.1 +/- 26.3 msec), cysts (284.1 +/- 38.2 msec) (p < 0.001). Logistic regression analysis indicated that lesion size and sex and age of patient were not significant independent predictors (p > 0.05). However, the combination of a history of malignancy, T2 value, and gadopentetate dimeglumine-enhancement pattern allowed generation of a prediction rule with an area under the receiver operating characteristic curve of 0.95. The patient's weight, lesion morphology, and cell type of the primary malignancy did not provide additional predictive information (p > 0.2). CONCLUSION: We recommend using the combination of T2 quantification and patient history of malignancy before deciding to administer gadopentetate dimeglumine for optimal lesion characterization, especially for equivocal lesions with T2 values between 90 and 130 msec. These factors allowed the construction of a prediction rule for lesion characterization.

Prediction rule for characterization of hepatic lesions revealed on MR imaging: estimation of malignancy. Publishing Authors By Initials

R Tello,HM Fenlon,T Gagliano,VL deCarvalho,EK Yucel,

For similar investigative techniques: epidemiologic methods: epidemiologic study characteristics as topic: epidemiologic studies: case-control studies: retrospective studies research abstracts see: investigative techniques: epidemiologic methods: epidemiologic study characteristics as topic: epidemiologic studies: case-control studies: retrospective studies research

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Prediction rule for characterization of hepatic lesions revealed on MR imaging: estimation of malignancy. Journal Published:

PUBLICATION TYPE: Research Support, U.S. Gov't,

Journal: AJR. American journal of roentgenology

VOLUME: 176

Page Numbers: 879-84

Journal Abbreviation:

ISSN: 0361-803X

DAY: 15

MONTH: Apr

YEAR: 2001

Prediction rule for characterization of hepatic lesions revealed on MR imaging: estimation of malignancy. Information

Number of References:

LANGUAGE: eng

NlmUniqueID: 7708173

Prediction rule for characterization of hepatic lesions revealed on MR imaging: estimation of malignancy. Keywords Mesh Terms:

KEYWORDS: Retrospective Studies

MESH TERMS: secondary

Chemical & Substance for Abstract: Prediction rule for characterization of hepatic lesions revealed on MR imaging: estimation of malignancy. Information

Substance Name: Gadolinium DTPA

Registry Number: 80529-93-7

Grant and Affiliation Information for Prediction rule for characterization of hepatic lesions revealed on MR imaging: estimation of malignancy.

AFFILIATION: Department of Radiology, Boston University School of Medicine, Boston Medical Center, 88 E. Newton St., Atrium 2, , MA 02118, USA.

Country: United States

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MEDLINETA: AJR Am J Roentgenol

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